Abstract

Social roles are a design option for robots that behave in accordance with user expectations. We believe that robots have to exceed stereotypical role behaviors and dynamically provide roles that suit the people's living conditions in order to achieve long-term acceptance. We are introducing a new user-focused design method to develop social role repertoires for adaptive human-robot interaction (HRI). The method consists of five sequential steps: (1) user group and application scenario identification; (2) acquisition of users' mental associations; (3) derivation of role traits; (4) prioritization of these traits; and (5) synthesis of an adaptive social role repertoire. We tested our method with two specific user groups: elder adults living at home and those living in care facilities. The results reveal basic role concepts and specific preference clusters in each user group. The empirically based clusters are suitable for the parameterizations and development of robots with adaptive social roles.

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